This discussion highlights the performance of deep learning models in mathematical assessments, particularly contrasting the capabilities of these models in solving novel problems versus their struggles with proof-based questions. There is an ongoing debate regarding the reliability of benchmark results and whether they accurately reflect the true potential and limitations of these AI systems. Commenters express skepticism about the concept of AGI and wonder about the practical implications of these findings on the typical user. The conversation stresses the necessity for critical evaluation of AI technologies and mentions the unpredictability surrounding their future developments.